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You will have track record of success in delivering new products, solving problems, and learning new technologies quickly. A commitment to teamwork, proactive approach to solving problems, and strong verbal and written communication skills are essential. Creating reliable, scalable, and high-performance products requires technical expertise, understanding of computer science fundamentals, and practical experience building efficient large-scale distributed systems. This person is comfortable delivering quality solutions in a fast-growing environment where priorities may change rapidly.
Key job responsibilities
* Build high-throughput, cost-effective data pipelines to support feature extraction and indexing for our web-scale Information Retrieval system
* Design and build cost-efficient distributed model training infrastructure
* Develop efficient, state-of-the-art streaming algorithms for processing large datasets (e.g. deduplication, topic clustering)
* Build on and maintain an existing code base as well as new components; maintain production code and contribute to deployment and QA processes
* Be involved in all stages of the software development cycle, including designing and developing new system architecture and improvements
* Participate in prioritization, estimation, and sprint planning
* Work in an Agile/Scrum environment to deliver high quality software against aggressive schedules
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Experience in Rust is highly desirablePursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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